Job Specifications
Our direct client is looking for Senior Applied AI Engineer to join the team on a full time direct hire.
This will be working 3 days week on site in San Diego, CA 92130
*** Local candidates only that is able to work 3 days onsite per week.
Applicants must be authorized to work for ANY employer in the U.S. Must have permanent authorization to work in the U.S.
The client is unable to sponsor or take over sponsorship of an employment Visa at this time.
Position Details
Senior Applied AI Engineer
Full Time – Direct Hire position.
Either Location: San Diego, CA 92130
Hybrid, 3 days week onsite.
Salary $120k - $150k + Bonus, equity and great Benefits
Travel may be required up to 5% of your time.
The Senior Applied AI Engineer builds and deploys AI solutions that directly support business workflows across Commercial, Regulatory, Quality, Finance, Operations, and Corporate functions. This role focuses on turning real business problems into working AI applications—including copilots, retrieval-augmented generation (RAG) solutions, document generation, automation agents, predictive models and decision-support tools.
The Senior Applied AI Engineer works closely with business SMEs, Data Engineering, and the AI Governance team to ensure solutions are secure, compliant, explainable, and production-ready in a regulated life-sciences environment.
SKILLS:
Required Qualifications
Bachelor’s degree in Computer Science, Engineering, Data Science, or related field
3–5 years of experience in software engineering, data engineering, or applied AI engineering
Strong proficiency in Python is required
Experience building and deploying applications using LLM APIs
Hands-on experience with ML frameworks (PyTorch, TensorFlow, scikit-learn)
Experience deploying AI solutions in cloud environments (Azure, AWS, or GCP)
Strong understanding of data engineering fundamentals, APIs, and distributed systems
Preferred Qualifications
Experience with RAG architectures, vector databases, and semantic search
Exposure to Azure OpenAI, Copilot Studio, LangChain, LlamaIndex, or similar frameworks
Familiarity with MLOps platforms (MLflow, SageMaker, Azure ML, Databricks)
Experience in regulated or data-sensitive environments (pharma, healthcare, finance)
Familiarity with AI governance, responsible AI, model explainability, and data classification
Experience building enterprise copilots or agentic AI solutions
Key Skills
Applied AI/ML & Prompt Engineering
Generative AI & LLM Integration
Enterprise Data Integration
API & Cloud Application Development
Security-aware Engineering
Business Problem Solving & Systems Thinking
Stakeholder Communication & Collaboration
RESPONSIBILITIES:
Applied AI Solution Development
Build AI applications such as copilots, search assistants, document intelligence/generation, workflow automation agents, predictive models and decision-support tools.
Implement RAG pipelines using enterprise data sources (SharePoint, data lake, document repositories, research systems, etc.)
Build and maintain end-to-end AI pipelines: data ingestion, feature engineering, model training, evaluation, deployment, and monitoring
Integrate LLMs via APIs and platforms (Azure OpenAI, OpenAI, Anthropic, AWS Bedrock) into business workflows
Develop prompt engineering, grounding, and evaluation frameworks to improve accuracy and reliability
Enterprise AI Enablement
Translate business use cases (e.g., medical affairs, regulatory, commercial, finance) into working AI prototypes and production apps
Collaborate with Data Scientists to translate models into scalable production systems
Collaborate with Product Owners and SMEs to refine requirements and success metrics
Build reusable AI components, prompt libraries, and solution patterns
Production & Platform Engineering
Deploy and maintain AI solutions using cloud platforms and modern APIs
Implement basic MLOps and LLMOps: versioning, monitoring, logging, performance tracking
Integrate with identity, access control, and data-security platforms (RBAC, Purview, etc.)
Implement logging, observability, performance tracking, and cost optimization for AI workloads
Ensure reliability, scalability, and security of AI systems in production environments
Governance & Compliance
Ensure AI solutions follow data classification, privacy, and AI governance policies
Support documentation for model usage, data sources, and risk assessments
Implement guardrails to prevent data leakage, hallucinations, and misuse
Must be able to pass and clear background check and Drug Test prior to starting.
The client Will Require 2 professional Work References to be completed prior to starting.
Applicants must be authorized to work for ANY employer in the U.S. Must have permanent authorization to work in the U.S.
The client is unable to sponsor or take over sponsorship of an employment Visa at this time.
If you are interested, please send me your updated Word Resume, along with your direct phone number and email.